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Document Title Author Full Name Author Short Name Index Corresponding Address ResearcherID ResearcherID Author Name ORCID ORCID Author Name Related Email
Machine learning models to predict the maximum severity of COVID-19 based on initial hospitalization record Lee, Chanhee Lee, C 3 Seoul Natl Univ, Interdisciplinary Program Bioinformat, Seoul, South Korea ksw2kms@knu.ac.kr;tspark@stats.snu.ac.kr;
Machine learning models to predict the maximum severity of COVID-19 based on initial hospitalization record Lee, Seungyeoun Lee, S 4 Sejong Univ, Dept Math & Stat, Seoul, South Korea ksw2kms@knu.ac.kr;tspark@stats.snu.ac.kr;
Machine learning models to predict the maximum severity of COVID-19 based on initial hospitalization record Oh, Bumjo Oh, B 5 Seoul Metropolitan Govt Seoul Natl Univ, Boramae Med Ctr, Dept Family Med, Seoul, South Korea O-2462-2017 Oh, Bumjo 0000-0002-2468-0755 Oh, Bumjo ksw2kms@knu.ac.kr;tspark@stats.snu.ac.kr;
Machine learning models to predict the maximum severity of COVID-19 based on initial hospitalization record Moon, Min Kyong Moon, MK 6 Seoul Metropolitan Govt Seoul Natl Univ, Boramae Med Ctr, Dept Internal Med, Seoul, South Korea AAE-7663-2020 Moon, Min ksw2kms@knu.ac.kr;tspark@stats.snu.ac.kr;
Machine learning models to predict the maximum severity of COVID-19 based on initial hospitalization record Moon, Min Kyong Moon, MK 6 Seoul Natl Univ, Coll Med, Dept Internal Med, Seoul, South Korea AAE-7663-2020 Moon, Min ksw2kms@knu.ac.kr;tspark@stats.snu.ac.kr;
Machine learning models to predict the maximum severity of COVID-19 based on initial hospitalization record Kim, Shin-Woo Kim, SW 7 교신저자 Kyungpook Natl Univ, Sch Med, Dept Internal Med, Daegu, South Korea AAB-4602-2022 Kim, Ji Hoon ksw2kms@knu.ac.kr;tspark@stats.snu.ac.kr;
Machine learning models to predict the maximum severity of COVID-19 based on initial hospitalization record Park, Taesung Park, T 8 교신저자 Seoul Natl Univ, Interdisciplinary Program Bioinformat, Seoul, South Korea ksw2kms@knu.ac.kr;tspark@stats.snu.ac.kr;
Machine learning models to predict the maximum severity of COVID-19 based on initial hospitalization record Park, Taesung Park, T 8 교신저자 Seoul Natl Univ, Dept Stat, Seoul, South Korea ksw2kms@knu.ac.kr;tspark@stats.snu.ac.kr;
Machine learning-based prediction model for late recurrence after surgery in patients with renal cell carcinoma Kim, Hyung Min Kim, HM 1 Catholic Univ Korea, Coll Med, Dept Med Informat, Seoul 06591, South Korea C-2026-2011 Kim, Sun toomey@catholic.ac.kr;
Machine learning-based prediction model for late recurrence after surgery in patients with renal cell carcinoma Kim, Hyung Min Kim, HM 1 Catholic Univ Korea, Coll Med, Dept Biomed & Hlth Sci, Seoul 06591, South Korea C-2026-2011 Kim, Sun toomey@catholic.ac.kr;
Machine learning-based prediction model for late recurrence after surgery in patients with renal cell carcinoma Byun, Seok-Soo Byun, SS 2 Seoul Natl Univ, Coll Med, Bundang Hosp, Dept Urol, Seongnam 13620, South Korea toomey@catholic.ac.kr;
Machine learning-based prediction model for late recurrence after surgery in patients with renal cell carcinoma Kim, Jung Kwon Kim, JK 3 Seoul Natl Univ, Coll Med, Bundang Hosp, Dept Urol, Seongnam 13620, South Korea toomey@catholic.ac.kr;
Machine learning-based prediction model for late recurrence after surgery in patients with renal cell carcinoma Jeong, Chang Wook Jeong, CW 4 Seoul Natl Univ, Seoul Natl Univ Hosp, Coll Med, Dept Urol, Seoul 03080, South Korea toomey@catholic.ac.kr;
Machine learning-based prediction model for late recurrence after surgery in patients with renal cell carcinoma Kwak, Cheol Kwak, C 5 Seoul Natl Univ, Seoul Natl Univ Hosp, Coll Med, Dept Urol, Seoul 03080, South Korea J-2731-2012 Kwak, Cheol 0000-0002-1987-2111 Kwak, Cheol toomey@catholic.ac.kr;
Machine learning-based prediction model for late recurrence after surgery in patients with renal cell carcinoma Hwang, Eu Chang Hwang, EC 6 Chonnam Natl Univ, Med Sch, Dept Urol, Gwangju 61469, South Korea K-3680-2019 Hwang, Eu toomey@catholic.ac.kr;
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